Study Guide

Objective

The participants learn how to analyze different types of data with different statistical tools. They learn how to identify suitable statistical techniques for their purposes and data

Content

Data description with numbers, percentages, descriptives and graphs
· Normal Distribution
· Examining the connection between variables with cross-tabs, grouped descriptives, correlation coefficients and scatter plots.
· Parametric and non-parametric tests and their limitations
· IBM SPSS Statistics and MS Excel are used as software
· Interpretation of the results obtained from the software

Materials

Materials in English
• Data Management Guidelines https://www.fsd.tuni.fi/en/services/data-management-guidelines/
• https://www.khanacademy.org/math/statistics-probability

Teaching methods

Remote meetings and assignments performed by oneself and the study group.

Exam schedules

Multiple choice test at the end of group meeting 3.5. (this forms 1/3 of the course grade)
The re-exam times are agreed with the teacher.

International connections

Learning-by-doing, flipped learning
The learning outcomes are mainly obtained through the participants self performance.
Skills learned in this course are the basic skills needed in research and development work.

Completion alternatives

-

Student workload

The course contains a starting info (1,5 h) and five half-day group meetings. There are independent tasks online between the meetings.
- The online platform of the course is opened in Itslearning 25.1.
- Online tasks related to the start up -meeting
• Participants own research topic and goals for the course (discussion in Itslearning)
• Survey about the participants own know-how about statistical methods
- Start up for the course 1.2. klo 12:30-14
- Online tasks related to the 1st group meeting
• Pre-assignment: Making a good questionnaire
- 1st group meeting online on 8.2. klo 12:30-16
• Feedback about the pre-assignment
• Research questions guiding the data collection
• Suitable questionnaire for statistical analysis: the right way to ask
• Personal data processing and ethics
• Preparation of the questionnaire – different kind of CASE examples
• Creating the questionnaire in Webropol
- Online tasks related to the 2nd group meeting
• Different scales of data and different analysis methods (test in Itslearning)
- 2nd group meeting online on 1.3. klo 12:30-16
• Feedback about the pre-assignment: Getting to know different analysis method
• Data transportation between the programmes: Webropol -> Excel -> SPSS
• Variable definitions in SPSS
• Creating sum variables
• Descriptive methods in SPSS and Excel
- Online tasks related to the 3rd group meeting
• Test on the associations between variables.
• Development of an analysis plan for given common data (group discussion in Itslearning)
- 3rd group meeting on 22.3. klo 12:30-16
• Implementing the data analysis with IBM SPSS Statistics and MS Excel
• Exploring the associations between variables with different methods
• Interpretation of the results obtained from the software
- Online tasks related to the 4th group meeting
• Test on normal distribution and statistical tests.
- 4th online group meeting on 12.4. klo 12:30-16
• Implementing the data analysis with IBM SPSS Statistics and MS Excel
• Statistical reasoning using normal distribution, confidence intervals and statistical tests
• Interpretation of the results obtained from the software
- Online tasks related to the 5th group meeting
• Data analysis for own data (online)
• Academic written report (MS Word) and a presentation (MS PowerPoint) of the results
- 5th online group meeting on 3.5. klo 12:30-16
• Presentations + questions & comments
- Online tasks after the 5th group meeting
• Peer and self-evaluation of the reports and the presentations
• Multiple choice –test

All the pre-tasks include studies of related theory and examples. This way they prepare to the multiple choice –test at the same time. (Time is included in the time given for the tasks.)

Content scheduling

Course Content
The participants learn how to analyze different types of data with different statistical tools. They learn how to identify suitable statistical techniques for their purposes and data.
• Data description with numbers, percentages, descriptives and graphs
• Examining the connection between variables with cross-tabs, grouped descriptives, box-plots, correlation coefficients and scatter plots.
• Normal Distribution
• Confidence intervals
• Parametric and non-parametric tests and their limitations
• Data analysis tools in IBM SPSS Statistics and MS Excel sotwares
• Interpretation of the results obtained from the software

Further information

Common announcements in Itslearning
Private messsages with email

Evaluation scale

H-5

Assessment methods and criteria

0 - 5:
Data analysis for own data (weight to grade 1:3)
Written report and PowerPoint presentation of the results (weight to grade 1:3)
Multiple choice –test (weight to grade 1:3)

Other assignments are evaluated with scale Approved/Failed (all the assignments must be approved for the course evaluation)